Data
clean1

clean1

active ARFF public Visibility: public Uploaded 06-04-2017 by Pieter Gijsbers
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Derived from the Musk dataset: https://www.openml.org/d/1116

169 features

class (target)nominal2 unique values
0 missing
molecule_namenumeric92 unique values
0 missing
conformation_namenumeric476 unique values
0 missing
f1numeric70 unique values
0 missing
f2numeric147 unique values
0 missing
f3numeric138 unique values
0 missing
f4numeric147 unique values
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f5numeric38 unique values
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f6numeric205 unique values
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f7numeric124 unique values
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f8numeric191 unique values
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f9numeric143 unique values
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f10numeric215 unique values
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f11numeric180 unique values
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f12numeric187 unique values
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f13numeric154 unique values
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f14numeric165 unique values
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f15numeric139 unique values
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f16numeric119 unique values
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f17numeric177 unique values
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f18numeric168 unique values
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f19numeric196 unique values
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f20numeric155 unique values
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f21numeric213 unique values
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f22numeric115 unique values
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f23numeric213 unique values
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f24numeric170 unique values
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f25numeric110 unique values
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f26numeric186 unique values
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f27numeric175 unique values
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f28numeric142 unique values
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f29numeric157 unique values
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f30numeric138 unique values
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f31numeric66 unique values
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f32numeric159 unique values
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f33numeric138 unique values
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f34numeric204 unique values
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f35numeric126 unique values
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f36numeric113 unique values
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f37numeric91 unique values
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f38numeric164 unique values
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f39numeric116 unique values
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f40numeric177 unique values
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f41numeric146 unique values
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f42numeric162 unique values
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f43numeric163 unique values
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f44numeric151 unique values
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f45numeric163 unique values
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f46numeric195 unique values
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f47numeric138 unique values
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f48numeric208 unique values
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f49numeric194 unique values
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f50numeric160 unique values
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f51numeric178 unique values
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f52numeric113 unique values
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f53numeric147 unique values
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f54numeric202 unique values
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f55numeric173 unique values
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f56numeric165 unique values
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f57numeric149 unique values
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f58numeric141 unique values
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f59numeric164 unique values
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f60numeric198 unique values
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f61numeric141 unique values
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f62numeric136 unique values
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f63numeric92 unique values
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f64numeric185 unique values
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f65numeric129 unique values
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f66numeric80 unique values
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f67numeric33 unique values
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f68numeric153 unique values
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f69numeric142 unique values
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f70numeric165 unique values
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f71numeric135 unique values
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f72numeric119 unique values
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f73numeric176 unique values
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f74numeric202 unique values
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f75numeric165 unique values
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f76numeric45 unique values
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f77numeric128 unique values
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f78numeric189 unique values
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f79numeric162 unique values
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f80numeric144 unique values
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f81numeric213 unique values
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f82numeric126 unique values
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f83numeric152 unique values
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f84numeric201 unique values
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f85numeric178 unique values
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f86numeric132 unique values
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f87numeric165 unique values
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f88numeric193 unique values
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f89numeric155 unique values
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f90numeric165 unique values
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f91numeric125 unique values
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f92numeric107 unique values
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f93numeric102 unique values
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f94numeric168 unique values
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f95numeric115 unique values
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f96numeric161 unique values
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f97numeric189 unique values
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f98numeric141 unique values
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f99numeric91 unique values
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f100numeric167 unique values
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f101numeric166 unique values
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f102numeric125 unique values
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f103numeric166 unique values
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f104numeric161 unique values
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f105numeric142 unique values
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f106numeric210 unique values
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f107numeric155 unique values
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f108numeric217 unique values
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f109numeric151 unique values
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f110numeric156 unique values
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f111numeric145 unique values
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f112numeric205 unique values
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f113numeric176 unique values
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f114numeric163 unique values
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f115numeric201 unique values
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f116numeric183 unique values
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f117numeric133 unique values
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f118numeric185 unique values
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f119numeric142 unique values
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f120numeric164 unique values
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f121numeric124 unique values
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f122numeric168 unique values
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f123numeric187 unique values
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f124numeric155 unique values
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f125numeric159 unique values
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f126numeric109 unique values
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f127numeric213 unique values
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f128numeric177 unique values
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f129numeric188 unique values
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f130numeric131 unique values
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f131numeric148 unique values
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f132numeric161 unique values
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f133numeric176 unique values
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f134numeric190 unique values
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f135numeric186 unique values
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f136numeric158 unique values
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f137numeric166 unique values
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f138numeric171 unique values
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f139numeric205 unique values
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f140numeric184 unique values
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f141numeric179 unique values
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f142numeric170 unique values
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f143numeric154 unique values
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f144numeric134 unique values
0 missing
f145numeric29 unique values
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f146numeric60 unique values
0 missing
f147numeric53 unique values
0 missing
f148numeric176 unique values
0 missing
f149numeric167 unique values
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f150numeric174 unique values
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f151numeric117 unique values
0 missing
f152numeric105 unique values
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f153numeric97 unique values
0 missing
f154numeric135 unique values
0 missing
f155numeric175 unique values
0 missing
f156numeric133 unique values
0 missing
f157numeric65 unique values
0 missing
f158numeric217 unique values
0 missing
f159numeric165 unique values
0 missing
f160numeric126 unique values
0 missing
f161numeric194 unique values
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f162numeric127 unique values
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f163numeric112 unique values
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f164numeric61 unique values
0 missing
f165numeric109 unique values
0 missing
f166numeric146 unique values
0 missing
Show first 100 features

62 properties

NumberOfInstances
476
Number of instances (rows) of the dataset.
NumberOfFeatures
169
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
168
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
ClassEntropy
0.99
Entropy of the target attribute values.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Dimensionality
0.36
Number of attributes divided by the number of instances.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
-0.43
Second quartile (Median) of kurtosis among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MeanSkewnessOfNumericAtts
0.28
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
-56.21
Second quartile (Median) of means among attributes of the numeric type.
MajorityClassPercentage
56.51
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
78.76
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
269
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
-0.06
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.59
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0.59
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
79.49
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
215.74
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-265.09
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
237.5
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
1.47
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
99.41
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
-14.18
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.83
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.59
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
13.58
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
11.96
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.5
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
137.55
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
43.49
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-1.04
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
93.72
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
207
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
-86.43
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
3.6
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
1
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
-50.57
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
-0.47
First quartile of skewness among attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
66.3
First quartile of standard deviation of attributes of the numeric type.
Show all 62 properties

22 tasks

Supervised Classification on clean1
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on clean1
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on clean1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on clean1
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
Clustering on clean1
0 runs - estimation_procedure: 50 times Clustering
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